babytreecc/ICLR2025review · Datasets at Hugging Face

uQEsLZU15E

Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate

main

Active

Large Vision-Language Models;Cross-Modal Alignment

foundation or frontier models, including LLMs

3;5;5;8

4;3;2;3

3;3;3;4

2;3;2;3

3;3;3;4

5.25

3

3.25

2.5

3.25

-0.396059

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "Thank you for your thoughtful reviews. We appreciate the opportunity to clarify key contribu...

uQRQo0cWZ6

Shake-It-Off: Jailbreaking Black-Box Large Language Models by Shaking Off Objectionable Semantics

main

Active

Jailbreaking Attacks;Large Language Models

foundation or frontier models, including LLMs

3;5;5;6

5;4;4;4

2;2;3;3

1;2;3;3

2;3;3;3

4.75

4.25

2.5

2.25

2.75

-0.927173

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uQjySppU9x

SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation

main

Active

zero-shot;tuning-free;self-guided;image-to-video diffusion;trajectory control

generative models

5;5;6;6;6

5;5;4;5;4

3;2;3;3;3

2;2;2;3;3

3;2;3;3;3

5.6

4.6

2.8

2.4

2.8

-0.666667

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

uQnvYP7yX9

ReNovo: Retrieval-Based \emph{De Novo} Mass Spectrometry Peptide Sequencing

main

Active

Peptide Sequencing

applications to physical sciences (physics, chemistry, biology, etc.)

5;5;5;6

4;4;4;4

2;3;3;2

3;2;2;3

2;3;4;2

5.25

4

2.5

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uREg3OHjLL

On the Expressiveness of Rational ReLU Neural Networks With Bounded Depth

main

Active

expressive power;depth;exact representations;ReLU networks;mixed volumes;lattice polytopes;number theory

learning theory

3;6;6;8;8

3;4;4;4;4

2;3;4;4;4

2;3;3;3;3

4;3;4;4;4

6.2

3.8

3.4

2.8

3.8

0.872872

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uSV07DapJx

Counterfactual Outcome Estimation in Time Series via Sub-treatment Group Alignment and Random Temporal Masking

main

Active

Counterfactual treatment effect estimation;Time series observational data;Confounding in time series;Sub-treatment Group Alignment;Random Temporal Masking

causal reasoning

3;5;5;5

3;4;4;4

2;2;2;2

2;3;2;2

2;2;2;3

4.5

3.75

2

2.25

1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uSg854MOWu

Understand Clean Generalization and Robust Overfitting in Adversarial Training from Two Theoretical Views: Representation Complexity and Training Dynamics

main

Active

deep learning theory;adversarial training;clean generalization and robust overfitting;representation complexity;training dynamics;feature learning theory

learning theory

5;5;5;6;6

3;3;4;2;4

2;2;3;3;3

2;2;2;3;3

3;2;2;3;3

5.4

3.2

2.6

2.4

2.6

-0.218218

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uSiyu6CLPh

AdCorDA: Classifier Refinement via Adversarial Correction and Domain Adaptation

main

Active

adversarial correction;domain adaptation;curriculum learning;adversarial attacks

transfer learning, meta learning, and lifelong learning

3;3;6;6

4;4;4;3

2;2;3;4

3;3;3;4

4.5

3.75

2.75

3.25

-0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uSz2K30RRd

Weighted Point Cloud Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric

main

Active

contrastive learning;multimodal representation learning;theoretical analysis;InfoNCE;pointwise mutual information

unsupervised, self-supervised, semi-supervised, and supervised representation learning

6;8;8

4;4;4

3;3;3

2;3;3

7.333333

4

3

2.666667

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uTqnyF0JNR

IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning

main

Active

imbalanced graph learning;graph class-imbalance;graph topology-imbalance;comprehensive benchmark

datasets and benchmarks

5;6;6

3;3;3

5.666667

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uUkpYafkVl

Conformal Prediction for Deep Classifier via Truncating

main

Active

Conformal Prediction;Uncertainty Quantification

interpretability and explainable AI

3;5;5;6

4;4;4;4

2;2;2;2

2;2;3;2

3;3;2;2

4.75

4

2

2.25

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uUsL07BsMA

Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning

main

Active

SAT Problem;Divide And Conquer;Graph Neural Network;Reinforcememt Learning

reinforcement learning

3;6;6;8

5;4;4;4

3;3;3;3

2;3;2;2

2;3;3;4

5.75

4.25

3

2.25

3

-0.889297

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uUsfvsrkOw

CRVR: Continuous Representation-Driven Video Frame Modulation Against rPPG Heart Rate Measurement

main

Withdraw

Adversarial video attack;Remote physiological heart rate measurement.

other topics in machine learning (i.e., none of the above)

Menglin Zhang;Xiaoxin Guo;Bohao Qu;Xiaofeng Cao;Di Lin;Shuifa Sun;Ivor Tsang;Qing Guo

~Menglin_Zhang1;~Xiaoxin_Guo1;~Bohao_Qu1;~Xiaofeng_Cao2;~Di_Lin3;~Shuifa_Sun1;~Ivor_Tsang1;~Qing_Guo3

3;3;3;5

5;5;3;5

2;2;2;3

2;2;3;2

2;2;2;3

3.5

4.5

2.25

0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "We would like to express our gratitude to the reviewers for their valuable feedback. After c...

uV3Gdoq2ez

Peer Review as A Multi-Turn and Long-Context Dialogue with Role-Based Interactions: Benchmarking Large Language Models

main

Active

peer review;large language models

datasets and benchmarks

3;5;5

5;4;4

2;3;3

2;1;4

1;3;3

4.333333

2.666667

2.333333

-1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uV9KFBVaFI

Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-Steering

main

Active

MLLMs; PEFTs; Representation Steering

foundation or frontier models, including LLMs

5;5;5;6

4;4;5;4

2;3;3;3

2;2;3;3

3;3;3;2

5.25

4.25

2.75

2.5

2.75

-0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

uVDwunWsLz

Benign Overfitting in Single-Head Attention

main

Active

single-head attention;benign overfitting;transformers

learning theory

3;3;5;6

4;3;4;2

3;2;3;3

2;2;2;3

3;2;3;3

4.25

3.25

2.75

2.25

2.75

-0.522233

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uVMZgtw2pf

CHG Shapley: Efficient Data Valuation and Selection towards Trustworthy Machine Learning

main

Active

Data Valuation;Shapley Value;Data selection

interpretability and explainable AI

3;3;5

3;4;4

3;4;2

2;1;2

3;4;2

3.666667

3

1.666667

3

0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uVm0zSNKkP

Skip the Steps: Data-Free Consistency Distillation for Diffusion-based Samplers

main

Active

Single-step sampling;Diffusion-based sampler;Distillation;Generative modeling;Optimal control

probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.)

3;3;3;5

4;3;3;4

2;2;2;2

1;1;2;2

3;2;3;3

3.5

2

1.5

2.75

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uW3tNSx7PZ

Gradients protection in federated learning for Biometric authentication

main

Active

federated learning;security;safety;facial authentication

alignment, fairness, safety, privacy, and societal considerations

1;1;3;5

4;5;5;3

1;2;2;3

2;2;2;2

1;1;2;3

2.5

4.25

2

1.75

-0.636364

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

uWMQxtmyYz

FedQLoRA: Federated Quantization-Aware LoRA for Large Language Models

main

Active

Quantization;LoRA;Large Language Models;Federated Learning

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;3;5;5

5;3;4;4

2;1;3;3

1;2;3;3

3;3;3;3

4

2.25

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uWUovmBRUq

Semantic or Covariate? A Study on the Intractable Case of Out-of-Distribution Detection

main

Active

Out-of-Distribution Detection;Definition;Theoretical Analysis

other topics in machine learning (i.e., none of the above)

3;3;5;5

3;4;3;4

1;2;2;3

1;2;2;2

2;2;3;3

4

3.5

2

1.75

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uWtLOy35WD

LLaVA-MoD: Making LLaVA Tiny via MoE-Knowledge Distillation

main

Active

MLLM;MoE;Distillation

applications to computer vision, audio, language, and other modalities

5;5;6;6;6;8

4;4;3;3;3;3

2;2;3;3;3;4

2;2;3;3;2;3

3;3;3;3;3;3

6

3.333333

2.833333

2.5

3

-0.707107

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uXLXq4ugAy

MULAN: Multimodal Protein Language Model for Sequence and Structure Encoding

main

Active

Protein language model;protein structure;multimodal model;downstream tasks

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;5;5;5

4;5;4;4

3;2;3;3

2;2;2;3

2;3;3;3

4.5

4.25

2.75

2.25

2.75

0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uXmRmaF5g0

LORA-MaOO: Learning Ordinal Relations and Angles for Expensive Many-Objective Optimization

main

Active

Expensive optimization;many-objective optimization;surrogate-assisted optimization;Gaussian Processes;ordinal regression

optimization

3;3;5;5

4;4;4;4

2;2;3;2

2;2;2;2

4

2.25

2

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uXytIlC1iQ

BrainGPT: A Brain-Inspired SNN-Based Large Language Model

main

Active

Spiking Neural Networks;Large Language Models;Spike-Timing-Dependent Plasticity;Neuromorphic Computing;ANN-to-SNN Conversion

foundation or frontier models, including LLMs

3;3;3;6

4;4;4;4

1;2;2;3

2;2;2;3

2;1;2;3

3.75

4

2

2.25

2

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "We greatly appreciate the reviewer's positive feedback and thoughtful questions. We would li...

uYAG9Gla5u

Multigraph Message Passing with Bi-Directional Multi-Edge Aggregations

main

Active

graph neural networks;multigraph;message passing;financial fraud detection

learning on graphs and other geometries & topologies

3;3;6;6

4;5;3;3

2;3;3;3

2;2;3;3

2;3;3;4

4.5

3.75

2.75

2.5

3

-0.904534

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "Thank you for the detailed response on the differences between multi-graphs and hypergraphs,...

uYzJvP8HGl

UMAP: A Highly Extensible and Physics-Based Simulation Environment for Multi-agent Reinforcement Learning

main

Active

multi-agent reinforcement learning;simulation environment;reinforcement learning

datasets and benchmarks

3;3;5;5;8;8

4;5;3;5;3;4

3;1;3;2;4;4

2;2;3;3;3;3

2;2;2;3;3;4

5.333333

4

2.833333

2.666667

-0.4967

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uZ5K4HeNwd

Beyond Auto-Regression: Fast LLMs via Self-Distillation Through Time

main

Active

language modeling;LLM;diffusion models;discrete diffusion models;diffusion language models;distillation

generative models

5;6;6;8

4;3;5;3

3;2;3;4

2;2;3;3

6.25

3.75

3

2.5

-0.4842

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

uZFXpPrwSh

Zero-shot Model-based Reinforcement Learning using Large Language Models

main

Active

Model-based Reinforcement Learning;Large language models;Zero-shot Learning;In-context Learning

learning on time series and dynamical systems

5;6;8;8

3;3;2;3

3;3;3;3

2;2;3;2

6.75

2.75

3

2.25

-0.555556

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uZVDJfV2Ex

A graph-based global optimization framework for problems with nonconvex norm constraints and penalty functions

main

Active

Norm Constraints;Sparse Parameter Estimation;Nonconvex Regularization;Global Optimization;Mixed-Integer Nonlinear Programs;Decision Diagrams

optimization

3;3;5

3;2;3

2;3;3

2;2;2

1;2;2

3.666667

2.666667

2

1.666667

0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "We have specifically addressed the \"weakness\" points raised in the review, which appear to...

uZgK0tcPqd

Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Models

main

Active

reward model;RLHF;visual attention;LLMs;eye tracking;implicit feedback

foundation or frontier models, including LLMs

3;6;8

3;4;3

2;3;3

3;3;3

2;3;4

5.666667

3.333333

2.666667

3

0.114708

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uZmmgHY1mD

The Perfect Blend: Redefining RLHF with Mixture of Judges

main

Active

Large Language Model;Reinforcement Learning from Human Feedback;Mixture of Judges;Constrained Policy Optimization

foundation or frontier models, including LLMs

3;6;6

4;4;3

2;3;3

2;4;3

5

3.666667

2.666667

3

-0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ua5MHdsbck

Data Distillation for extrapolative protein design through exact preference optimization

main

Active

Protein design;Protein Language Models;Preference Learning;Extrapolation;Data distillation

applications to physical sciences (physics, chemistry, biology, etc.)

5;5;6;6

3;3;3;3

2;3;3;3

3;3;3;2

2;3;3;2

5.5

3

2.75

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uaGNerHa1J

Efficient Newton-type Federated Learning with Non-IID Data

main

Active

Federated learning;Newton-type optimization;Generalization analysis;Integral operator theory

learning theory

3;5;6

3;3;3

3;2;4

2;2;4

4;3;3

4.666667

3

2.666667

3.333333

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uaKBM9sGEm

Towards Off-Road Autonomous Driving via Planner Guided Policy Optimization

main

Active

Reinforcement learning;Learning from Demonstrations;Autonomous driving;Off-road driving

applications to robotics, autonomy, planning

1;3;6;6

4;3;3;3

1;3;3;3

2;2;2;3

1;3;3;3

4

3.25

2.5

2.25

2.5

-0.816497

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uaMSBJDnRv

Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization

main

Active

Direct Preference Optimization;DPO;Likelihood Displacement;Unalignment;Alignment;Language Models

foundation or frontier models, including LLMs

5;6;6;8

3;3;3;3

3;3;4;3

2;3;3;3

4;3;4;3

6.25

3

3.25

2.75

3.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ubIxE93FLM

Visually Descriptive Language Model for Vector Graphics Reasoning

main

Active

Large Multimodal Model;Large Language Model;Vector Graphics;Low-level Perception;Low-level Visual Reasoning

foundation or frontier models, including LLMs

3;5;5;5

4;4;4;2

2;3;3;3

3;2;3;2

2;3;3;3

4.5

3.5

2.75

2.5

2.75

-0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": null, "confidence": null, "contribution": null, "desk_reject_comments": null, "details_of_ethi...

ubUTIlAH0m

Multi-Physics Operator Network for In-context learning (m-PhOeNIX)

main

Active

Multi-physics operator learning;neural operator;catastrophic forgetting;continual learning;wavelet

transfer learning, meta learning, and lifelong learning

3;5;5

5;3;4

2;3;4

2;3;2

3;2;3

4.333333

4

3

2.333333

2.666667

-0.866025

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "Dear authors and AC,\nWith the release of the reviews, I realized that I mistakenly swapped ...

ubuGgIPVD0

TSTTC: A Large-Scale Dataset for Time-to-Contact Estimation in Driving Scenarios

main

Active

Time-to-Contact Estimation;Dataset

datasets and benchmarks

5;5;5;5

3;5;4;4

3;2;2;3

3;2;3;2

3;2;2;3

5

4

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ud8FtE1N4N

Rethinking Sparse Scaling through the Lens of Average Active Parameter Count

main

Active

pruning;sparsity;large language model;pretraining

foundation or frontier models, including LLMs

5;6;8

3;4;4

3;3;4

2;3;3

3;4;3

6.333333

3.666667

3.333333

2.666667

3.333333

0.755929

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

udfjje2xXb

Kolmogorov–Arnold Graph Neural Networks

main

Active

Graph Neural Networks;Kolmogorov-Arnold Networks;Interpretability

learning on graphs and other geometries & topologies

1;3;3;3;5

5;3;4;4;4

2;2;1;3;2

2;2;2;3;2

2;2;4;3;2

3

4

2

2.2

2.6

-0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

udtrtwkvk5

Subspace Optimiztion for Large Language Models with Convergence Guarantees

main

Active

Large Language Models;Memory-Efficient Training;Subspace Learning

optimization

3;5;5;5

3;4;4;3

2;3;3;2

2;2;3;3

1;3;3;3

4.5

3.5

2.5

0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ue1Tt3h1VC

Multiple Heads are Better than One: Mixture of Modality Knowledge Experts for Entity Representation Learning

main

Active

Multi-modal Information Fusion;Knowledge Graph;Multi-modal Entity Representation;Mixture-of-Experts

applications to computer vision, audio, language, and other modalities

5;6;6;6;6

4;4;4;2;4

2;3;3;3;3

2;3;2;3;3

2;3;3;4;3

5.8

3.6

2.8

2.6

3

-0.25

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ueeqGvQozB

ML4MILP: A Benchmark Dataset for Machine Learning-based Mixed-Integer Linear Programming

main

Active

Mixed Integer Linear Programming;Machine Learning;Benchmark Dataset

datasets and benchmarks

3;3;3;6

4;4;4;3

2;2;2;3

2;2;1;3

3;2;1;2

3.75

2.25

2

-1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uffmkDtlR2

MIMOSA: Multimodal Concept-based representations

main

Active

Concept-based model;Multimodal;Explainability

interpretability and explainable AI

1;3;3;3;8

4;4;5;4;4

1;3;2;2;3

1;3;1;2;2

3.6

4.2

2.2

1.8

-0.128624

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ufhrQG5xie

POIL: Preference Optimization for Imitation Learning

main

Active

Offline Imitation Learning;Preference-based Reinforcement Learning;Large Language Model Alignment;Data Efficiency

reinforcement learning

3;5;5;8;8

5;3;3;3;4

2;2;3;3;3

1;3;2;4;3

3;3;2;4;3

5.8

3.6

2.6

3

-0.438354

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ufi0WPTgWp

Enhancing Multimodal LLM for Detailed and Accurate Video Captioning using Multi-Round Preference Optimization

main

Active

Multi-modal large language models;video captioning;multi-round DPO;rebirth tuning

applications to computer vision, audio, language, and other modalities

3;3;5;5

4;5;5;4

2;3;3;2

2;3;2;2

1;3;2;3

4

4.5

2.5

2.25

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

ugXGFCS6HK

Discriminating image representations with principal distortions

main

Active

representational similarity metric; Fisher information; information geometry; perception

applications to neuroscience & cognitive science

5;5;6;6;8

4;3;3;3;4

3;3;4;3;4

2;3;3;3;3

3;4;3;3;4

6

3.4

2.8

3.4

0.372678

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

ugyqNEOjoU

ScImage: How good are multimodal large language models at scientific text-to-image generation?

main

Active

LLMs;multimodality;science;image generation

datasets and benchmarks

3;3;6

4;4;4

2;1;2

2;2;3

2;3;3

4

1.666667

2.333333

2.666667

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uhaLuZcCjH

Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks

main

Active

alignment;optimization

alignment, fairness, safety, privacy, and societal considerations

3;3;6;6

4;3;2;2

2;2;3;3

2;3;3;3

2;1;3;3

4.5

2.75

2.5

2.75

2.25

-0.904534

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

uiBLOcyTIA

NEXTLOCLLM: NEXT LOCATION PREDICTION USING LLMS

main

Active

next location prediction;large language model;zero-shot

foundation or frontier models, including LLMs

3;5;5;6

4;4;4;5

2;3;2;3

2;2;3;3

2;3;3;4

4.75

4.25

2.5

3

0.662266

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uinsufj5TR

Enabling Sparse Autoencoders for Topic Alignment in Large Language Models

main

Active

Alignment;SAEs;Mechanistic Interpretability;Large Language Models

interpretability and explainable AI

1;3;3;6;8

5;3;3;2;3

1;2;3;2;3

1;2;2;3;3

1;3;2;2;4

4.2

3.2

2.2

2.4

-0.6744

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": null, "code_of_ethics": null, "comment": { "value": "For anonymization, we used the standard anonymization platform (anonymous.4open.science) and...

uiyljVIP0k

UNIFYING LONG AND SHORT SPATIO-TEMPORAL FORECASTING WITH SPECTRAL GRAPH NEURAL NETWORKS

main

Active

multivariate time series forecasting;spatio-temporal graph neural network;spectral graph neural network

learning on time series and dynamical systems

3;3;5;6;8

4;4;4;4;5

2;1;2;3;3

2;1;2;2;3

1;1;3;2;3

5

4.2

2.2

2

0.790569

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ujNe7sybJu

Realizing Video Summarization from the Path of Language-based Semantic Understanding

main

Active

Visual Language Model;Large Language Model;Video Summarization;Video Understanding;VideoLLM

applications to computer vision, audio, language, and other modalities

1;3;3;3

5;4;4;5

3;3;2;3

1;2;1;2

1;3;2;2

2.5

4.5

2.75

1.5

2

-0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

ujpAYpFDEA

Can Watermarked LLMs be Identified by Users via Crafted Prompts?

main

Active

Large Language Models;Watermark;Identification

alignment, fairness, safety, privacy, and societal considerations

5;5;6;8

3;4;3;4

2;3;3;4

2;2;3;4

3;3;3;4

6

3.5

3

2.75

3.25

0.408248

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ukmWcHpa3H

Meta-weighted Diffusion Model for Reliable Online Surgical Phase Recognition

main

Active

surgical phase recognition;diffusion model;meta learning

transfer learning, meta learning, and lifelong learning

5;5;5;5

4;3;5;2

4;2;3;3

3;2;3;3

3;1;4;2

5

3.5

3

2.75

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

ulCAPXYXfa

OmniKV: Dynamic Context Selection for Efficient Long-Context LLMs

main

Active

Efficient LLMs;KV cache;Long Context LLMs

foundation or frontier models, including LLMs

3;5;5;6

4;4;5;2

2;2;2;3

3;3;2;3

4.75

3.75

2.25

2.75

-0.473684

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 2 }, "contribution": { "value":...

ulGwcj1egv

FiRST: Finetuning Router-Selective Transformers for Input-Adaptive Latency Reduction

main

Active

Input-Adaptive Layer Selection; Resource-Constrained Environments; Latency Reduction; Finetuning

generative models

3;3;3;3

5;4;4;5

2;2;2;2

2;2;2;3

2;3;3;2

3

4.5

2

2.25

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

ulIW7Frjpn

Large Language Models Are Stronger Entropy Models for Transform Coding

main

Active

Transform Coding;Multimodal Data Compression;Entropy Model;Large Language Models

applications to computer vision, audio, language, and other modalities

3;5;5;6

5;4;4;4

3;3;2;3

2;2;2;3

2;3;2;3

4.75

4.25

2.75

2.25

2.5

-0.927173

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

ulJNq6FQrw

Progressively Label Enhancement for Large Language Model Alignment

main

Active

Large Language Model;LLM Alignment

alignment, fairness, safety, privacy, and societal considerations

3;5;5;5;5

3;4;3;3;4

2;2;2;2;2

2;2;2;2;3

2;3;3;2;2

4.6

3.4

2

2.2

2.4

0.408248

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

ulXCYmvVg6

Effi-Code: Unleashing Code Efficiency in Language Models

main

Active

Large Langugae Models;Code Generation;Program Synthesis;Efficient Method;Alignment

foundation or frontier models, including LLMs

1;3;5;6

5;5;3;4

1;3;2;3

1;1;2;3

2;3;3;3

3.75

4.25

2.25

1.75

2.75

-0.745815

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

umggmAFhRD

Towards shutdownable agents via stochastic choice

main

Active

the alignment problem;the shutdown problem;corrigibility;reinforcement learning;stochastic policy

alignment, fairness, safety, privacy, and societal considerations

3;3;5;5

4;3;3;2

2;1;2;2

1;1;2;3

3;3;3;3

4

3

1.75

3

-0.707107

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

un9Gzm0BZb

ER-AAE: A quantum state preparation approach based on entropy reduction

main

Active

quantum machine learning;amplitude encoding;state preparation

other topics in machine learning (i.e., none of the above)

3;3;5;6

5;5;5;4

3;2;2;3

2;2;2;3

3;4;3;3

4.25

4.75

2.5

2.25

3.25

-0.777778

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

unDQOUah0F

VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks

main

Active

agents;benchmark;video understanding;multimodal agents

datasets and benchmarks

5;6;6;6

3;4;3;3

2;3;3;3

3;2;3;3

3;3;2;3

5.75

3.25

2.75

0.333333

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uo6UsVkkEQ

MolReFlect: Towards Fine-grained In-Context Alignment between Molecules and Texts

main

Active

Large Language Models;In-Context Tuning;Reflection Tuning;Molecule Discovery;Molecule-Text Alignment

applications to physical sciences (physics, chemistry, biology, etc.)

3;5;5;6

4;3;3;4

2;2;2;3

2;2;2;2

3;2;3;3

4.75

3.5

2.25

2

2.75

-0.229416

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uo8PO6Ah59

CellPainTR: Contrastive Batch Corrected Transformer for Large Scale Cell Painting

main

Active

Cell Painting;Batch Correction;Representation Learning;Transformer;Hyena Operator;High-dimensional Data;Image-based Profiling

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;5;5;6

3;5;5;4

2;3;3;4

2;2;2;3

3;3;1;3

4.75

4.25

3

2.25

2.5

0.622543

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

uoU4ypjAmN

SPD: Sync-Point Drop for efficient tensor parallelism of Large Language Models

main

Active

sync point drop;tensor parallelism;distributed inference;efficient ml

optimization

3;3;5;5

4;3;5;4

2;2;2;3

2;2;4;3

1;3;3;3

4

2.25

2.75

2.5

0.707107

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uogG8BfLs2

Weak-to-Strong Generalization Through the Data-Centric Lens

main

Active

weak to strong generalization;data-centric AI

foundation or frontier models, including LLMs

6;6;6;8

3;3;3;2

3;4;3;3

3;2;3;4

6.5

2.75

3.25

3

-1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

upALuXjdxc

Error Slice Discovery via Manifold Compactness

main

Active

Error Slice Discovery;Manifold Compactness;Model Evaluation

interpretability and explainable AI

3;5;6;6

4;4;4;3

2;2;3;3

2;3;3;3

3;3;3;2

5

3.75

2.5

2.75

-0.471405

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

upV91V0Big

Continual Task Learning through Adaptive Policy Self-Composition

main

Active

continual learning;offline reinforcement learning

transfer learning, meta learning, and lifelong learning

3;5;5;6

4;3;3;3

3;3;2;4

2;2;2;2

3;2;3;4

4.75

3.25

3

2

3

-0.927173

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

upkxzurnLC

Learning on One Mode: Addressing Multi-Modality in Offline Reinforcement Learning

main

Active

Offline reinforcement learning;weighted imitation learning;multi-modality.

reinforcement learning

3;3;5;8

2;3;3;3

2;3;2;3

1;3;3;3

3;3;2;3

4.75

2.75

2.5

2.75

0.493742

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

upoxXRRTQ2

The impact of allocation strategies in subset learning on the expressive power of neural networks

main

Active

subset learning;theoretical neuroscience;expressive power;neural networks;recurrent neural network

applications to neuroscience & cognitive science

1;3;5;8

4;4;4;4

2;3;3;4

1;1;2;4

2;3;3;4

4.25

4

3

2

3

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

upzyG4wRBr

Program Synthesis Benchmark for Visual Programming in XLogoOnline Environment

main

Active

Program Synthesis;Visual Programming;Large Language Models;Multimodal Models;Spatial Reasoning

datasets and benchmarks

3;3;3;8;8

5;3;4;4;4

2;2;3;3;4

2;2;2;3;3

2;3;4;4;4

5

4

2.8

2.4

3.4

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uq9TLFT7tF

EG4D: Explicit Generation of 4D Object without Score Distillation

main

Active

4D Generation

generative models

5;5;6

5;4;4

2;2;3

2;3;3

3;3;3

5.333333

4.333333

2.333333

2.666667

3

-0.5

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uqG0kFLccD

ESCAPE: Equivariant Shape Completion via Anchor Point Encoding

main

Active

3D Shape Completion;Rotation Equivariance

applications to computer vision, audio, language, and other modalities

3;3;3;5

3;4;5;4

3;2;2;3

2;1;2;4

1;2;3;2

3.5

4

2.5

2.25

2

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 5 }, "contribution": { "value":...

uqLQjtSdFN

Functional Gradients and Generalizations for Transformer In-Context Learning

main

Active

Transformer;in-context learning

interpretability and explainable AI

3;3;3;3;3;5;5

3;4;3;3;4;2;3

2;2;2;2;2;2;3

2;1;1;1;1;2;2

1;2;2;2;1;1;2

3.571429

3.142857

2.142857

1.428571

1.571429

-0.636396

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uqWM9hBDAE

How Much is Unseen Depends Chiefly on Information About the Seen

main

Active

Good-Turing frequency estimation;Multinomial probability estimation;Unseen events;Missing mass;Probability mass

learning theory

6;8;8

4;3;2

3;4;3

3;2;3

3;4;3

7.333333

3

3.333333

2.666667

3.333333

-0.866025

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uqe5HkjbT9

Trajectory-Class-Aware Multi-Agent Reinforcement Learning

main

Active

trajectory clustering;multi-agent reinforcement learning;trajectory-class-aware policy

reinforcement learning

5;6;6

3;4;4

2;3;2

2;3;3

5.666667

3.666667

2.333333

2.666667

1

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

urQi0TgXFY

Hidden in Plain Text: Emergence & Mitigation of Steganographic Collusion in LLMs

main

Active

Large Language Models;Steganography;Collusion;Reinforcement Learning;In-Context Learning;Multi-agent Systems

alignment, fairness, safety, privacy, and societal considerations

3;3;6;6

5;4;4;3

3;2;3;3

1;2;3;3

3;2;4;3

4.5

4

2.75

2.25

3

-0.707107

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

urcEYsZOBz

Latent-EnSF: A Latent Ensemble Score Filter for High-Dimensional Data Assimilation with Sparse Observation Data

main

Active

Data Assimilation;Score Based Models;Diffusion Models;Weather Forecasting

learning on time series and dynamical systems

3;3;5;5;6;6

4;3;4;4;3;4

2;2;2;3;3;3

2;1;2;2;3;3

1;2;2;3;3;3

4.666667

3.666667

2.5

2.166667

2.333333

0.094491

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urf8a5G59f

X-Diffusion: Generating Detailed 3D MRI Volumes From a Single Image Using Cross-Sectional Diffusion Models

main

Active

MRI reconstruction;diffusion models;latent diffusions

applications to physical sciences (physics, chemistry, biology, etc.)

3;3;6;6

5;4;4;3

2;2;3;3

2;2;2;3

2;1;4;3

4.5

4

2.5

2.25

2.5

-0.707107

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ursX3k1rTO

Wyckoff Transformer: Generation of Symmetric Crystals

main

Active

material design;machine learning;crystal generation;space group symmetry;Transformer;Wyckoff position;generative model;autoregressive model;permutation invariance

applications to physical sciences (physics, chemistry, biology, etc.)

3;3;5;5;6

4;4;3;3;4

1;2;3;2;3

2;3;3;3;3

1;1;2;3;2

4.4

3.6

2.2

2.8

1.8

-0.408248

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us5riDkeBW

Social Learning: Towards Collaborative Learning with Large Language Models

main

Active

language models;privacy-aware knowledge transfer

generative models

3;3;5;5

3;4;3;4

1;2;3;3

3;2;2;2

4

3.5

2.25

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

usFdPd4Ghs

Deep Kernel Posterior Learning under Infinite Variance Prior Weights

main

Active

Kernel methods;Deep Gaussian processes;Infinite variance priors;Deep Bayesian neural networks

probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.)

5;5;6;6;8

3;2;2;3;4

2;3;3;3;3

2;2;3;2;3

6

2.8

2.4

0.731925

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usX2ixXopC

Measurement information multiple-reuse allows deeper quantum transformer

main

Active

quantum machine learning;quantum transformer;measurement information multiple reuse

foundation or frontier models, including LLMs

3;3;5;5

3;5;4;4

2;2;3;2

2;1;2;1

2;2;3;3

4

2.25

1.5

2.5

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uswS6tUCN2

Magnituder Layers for Implicit Neural Representations in 3D

main

Active

NeRF;SDF;Implicit Representations

unsupervised, self-supervised, semi-supervised, and supervised representation learning

3;3;5

4;3;3

2;2;2

2;2;3

3.666667

3.333333

2

2.333333

-0.5

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

utkGLDSNOk

TODO: Enhancing LLM Alignment with Ternary Preferences

main

Active

LLM;Preference alignment;Ternary Preference

alignment, fairness, safety, privacy, and societal considerations

3;5;6;8

3;5;4;3

3;2;3;3

2;3;3;3

3;3;3;3

5.5

3.75

2.75

3

-0.083624

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utz99dx2RN

VAE-Var: Variational Autoencoder-Enhanced Variational Methods for Data Assimilation in Meteorology

main

Active

Data assimilation;Variational Autoencoder;Weather Forecasting

applications to physical sciences (physics, chemistry, biology, etc.)

3;3;3;6;8;8

3;5;4;4;2;5

2;2;3;3;3;3

2;2;2;3;3;3

3;3;2;3;4;4

5.166667

3.833333

2.666667

2.5

3.166667

-0.195196

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uu2CorJCUi

Adaptive Curvature Step Size: A Path Geometry Based Approach to Optimization

main

Active

Adaptive Curvature Step Size (ACSS);Adaptive learning rate;Radius of curvature step size;Low-memory optimization;Path geometry;Convergence analysis;PyTorch optimizers;SGD enhancement

optimization

3;5;5;6;8

5;4;3;4;3

1;2;3;4;2

2;3;2;3;2

2;2;3;4;3

5.4

3.8

2.4

2.8

-0.756644

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uuCcK4cmlH

IDS-Agent: An LLM Agent for Explainable Intrusion Detection in IoT Networks

main

Active

intrusion detection;LLM agent;internet of things;LLM

foundation or frontier models, including LLMs

3;3;3

4;4;4

2;3;2

2;2;2

2;3;3

3

4

2.333333

2

2.666667

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uuCgIHqxpr

Real-World Data and Calibrated Simulation Suite for Offline Training of Reinforcement Learning Agents to Optimize Energy and Emission in Buildings for Environmental Sustainability

main

Active

Reinforcement Learning;HVAC Control;Simulator;RL Environment;Environmental Sustainability;Climate;Time-series prediction

datasets and benchmarks

3;3;5;5

4;5;4;4

1;2;3;2

1;2;3;3

4

4.25

2

2.25

-0.57735

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uuEQsqb0GH

Avoiding Catastrophe in Online Learning by Asking for Help

main

Active

online learning;AI safety;asking for help;irreversibility

learning theory

5;5;6;6

3;3;2;3

3;3;3;3

2;2;3;2

3;3;3;2

5.5

2.75

3

2.25

2.75

-0.57735

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uuOmdQy6p7

Few-shot Text Adversarial Attack for Black-box Multi-task Learning

main

Active

multi-task adversarial text attacks

alignment, fairness, safety, privacy, and societal considerations

1;5;5;6

4;3;4;2

1;3;3;4

1;3;2;3

2;3;3;3

4.25

3.25

2.75

2.25

2.75

-0.667308

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uuPkll6i7m

Towards Certification of Uncertainty Calibration under Adversarial Attacks

main

Active

Machine Learning;Adversarial Robustness;Certification;Adversarial Training;Uncertainty Quantification;Calibration;Deep Learning;Certified Calibration

alignment, fairness, safety, privacy, and societal considerations

5;5;6;8

4;3;4;4

2;3;4;3

3;3;4;3

6

3.75

3

3.25

0.471405

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uuXPWRtwvK

Graph-based Confidence Calibration for Large Language Models

main

Active

Language Models; Uncertainty Calibration

foundation or frontier models, including LLMs

3;3;5;5

4;5;5;3

2;3;3;2

2;2;3;2

2;3;3;2

4

4.25

2.5

2.25

2.5

-0.301511

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 3 }, "contribution": { "value":...

uuef1HP6X7

IDIV: Intrinsic Decomposition for Arbitrary Number of Input Views and Illuminations

main

Active

inverse rendering;diffusion models;intrinsic decomposition

generative models

3;5;6;6;8

5;5;4;5;4

2;3;3;3;4

2;3;3;3;3

3;3;2;2;4

5.6

4.6

3

2.8

-0.703526

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uuriavczkL

Counterfactual Realizability

main

Active

causal inference;experiment design;causal reinforcement learning;counterfactual reasoning

causal reasoning

5;6;8;8

2;4;4;4

3;3;3;3

2;3;4;3

2;2;3;3

6.75

3.5

3

2.5

0.777778

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uuvujfQXZy

Selective Concept Bottleneck Models Without Predefined Concepts

main

Active

interpretability;concept bottleneck models;concepts

interpretability and explainable AI

3;5;5

4;4;4

3;3;3

2;2;2

3;2;3

4.333333

4

3

2

2.666667

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uvHmnahyp1

SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints

main

Active

GFlowNets;de novo molecular generation;synthesizable molecular design

applications to physical sciences (physics, chemistry, biology, etc.)

5;5;6;6

4;4;4;4

2;3;2;3

3;3;2;4

3;3;2;3

5.5

4

2.5

3

2.75

0

[ { "TLDR": null, "_bibtex": null, "abstract": null, "anonymous_url": null, "authorids": null, "authors": null, "code_of_conduct": { "value": "Yes" }, "code_of_ethics": null, "comment": null, "confidence": { "value": 4 }, "contribution": { "value":...

uwzyMFwyOO

Learning Latent Graph Structures and their Uncertainty

main

Active

Graph Structure Learning;Graph Neural Networks;Latent Distribution Calibration;Discrete Random Variables

learning on graphs and other geometries & topologies

3;5;5;5;5

4;3;3;3;3

2;4;3;3;2

2;2;3;3;3

3;3;3;3;2

4.6

3.2

2.8

2.6

2.8

-1

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